Remote Detection Method for Metering Inaccuracy of EV Charging Stations Based on Ridge Regression

In response to the high cost and low efficiency of current electric vehicle (EV) charging station metering performance detection, this article proposes a method for detecting metering inaccuracy of charging stations based on ridge regression, utilizing remotely collected electricity consumption data. This article first establishes a parameter identification model for ac/dc mixed charging stations and line loss based on the power topology of charging stations and the working principles of charging piles. Then, the ridge regression method based on a robust standard deviation (RSD) parameter search strategy is employed to solve the model, effectively addressing the issue of multicollinearity in charging pile data. Finally, through simulation and actual real scenarios, this article validates and compares the method, confirming the effectiveness and superiority of the proposed approach. This research provides a data-driven theoretical framework and practical solution for the metering performance detection of EV charging stations.